4 citations · 4 across the 8 of their papers we have counts for
8 papers
PlannerForge: LLM Agents for Scenario-Based Testing of Motion Planners in Autonomous Driving
Yuan Gao, Sebastian Müller, Mattia Piccinini +5
Ensuring the safety of autonomous driving is a critical challenge. Scenario-based testing is a systematic process used to validate Autonomous Driving Systems (ADSs), but it remains…
In the Driver's Seat: A Multi-Company Study on the Reality of Autonomous Driving System Testing
Qunying Song, Yuan Gao, Johannes Betz +3
Autonomous driving systems (ADS) are rapidly advancing and increasingly deployed in real-world applications. This creates growing demands for effective testing to ensure system fun…
Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving
Yuan Gao, Wenting Miao, Mattia Piccinini +3
Validating autonomous driving systems requires diverse, regulation-compliant test scenarios. In simulation-based testing, scenarios are defined as executable scripts. Yet automatic…
From Research to Practice: An Interactive Rapid Review of Autonomous Driving System Testing in Industry
Qunying Song, Ali Nouri, Håkan Sivencrona +1
Autonomous driving systems (ADS) are increasingly deployed in real traffic, yet testing remains fundamentally challenging due to open environments, complex scenarios, and the lack…
Generative AI for Testing of Autonomous Driving Systems: A Survey
Qunying Song, He Ye, Mark Harman +1
Autonomous driving systems (ADS) have been an active area of research, with the potential to deliver significant benefits to society. However, before large-scale deployment on publ…
Industry Practices for Challenging Autonomous Driving Systems with Critical Scenarios
Qunying Song, Emelie Engström, Per Runeson
Testing autonomous driving systems for safety and reliability is extremely complex. A primary challenge is identifying the relevant test scenarios, especially the critical ones tha…